Wireless location/positioning techniques, commonly referred to as “radiolocation” or “geolocation”, which is typically given in terms of geographic coordinates, refers to the method of obtaining the positional information of a device using wireless systems. For example, wireless positioning techniques used to determine the location of radio devices, and have resulted in a multitude of new applications and services such as outdoor person/asset tracking, enhanced 911 services, location sensitive billing, fraud protection, fleet management, intelligent transportation systems, cellular system design and management, and mobile yellow pages. One form of wireless location technology, known as infrastructure wireless systems, can be divided into two main categories:                hand-set based systems, which determine the location of a hand-held radiodevice (e.g. a GPS receiver or a cellular phone) by having the hand-held device receive and process signals received from pre-determined reference stations (e.g. global navigation satellite systems, base stations and/or wireless access points) to determine its location; and        network-based systems, which attempt to determine the position of a device by measuring and processing its signal parameters as they are received at pre-determined reference stations.        
Different positioning techniques for locating or “fixing” wireless devices within infrastructure systems are known, particularly where the device is capable of receiving/transmitting a radio signal transmitted/received from/by reference stations having a known position. For instance, localization of a device in infrastructure based systems may be achieved by estimating ranges (i.e. distances) between the device to be located/positioned and the reference stations using known “ranging measurement techniques” such as, for example, Received Signal Strength, Time-Of-Arrival, Round Trip Delay, and Time-Difference-Of-Arrival based techniques.
These techniques, however, can suffer from ranging (propagation delay) errors, and it is therefore a main objective of a positioning technique to minimize the effect of the ranging measurement error on the positioning error. For instance, processing propagation delay estimates from “direct path” signals can be an effective ranging measurement technique for more accurately positioning a wireless device. However, large ranging errors can arise, over “multipath” signals, or in circumstances where the Signal-to-Noise Ratio (SNR) received by the device is weak.
Numerous attempts have been made to mitigate large propagation delay errors, such as, for example:                limiting the received signal strength (i.e. SNR) to a certain SNR threshold value which should be above the SNR value of the threshold region; or        accumulating the received signal in an attempt to increase the received SNR value to be greater than the SNR value of the threshold region.        
Other known techniques for mitigating large propagation delay errors include the use of robust estimation techniques (e.g. M-estimator) at the positioning/navigation stage to provide robustness against biased propagation delay errors, where the errors might arise due to propagation delay being estimated from weak signals. However, such techniques provide robustness against propagation delay bias at the cost of degrading the positioning accuracy. In addition, some of these techniques require a predetermined value, which can vary depending upon the propagation environment. Indeed, some studies examining Cramer-Rao Lower Bound (CRLB) have recommended the detection and rejection of propagation delay observations having large delay errors (i.e. bias), rather than estimating and removing their respective biases. However, the distribution of the propagation delay (i.e. pseudorange) measurement hypothesis is usually unknown.
There is a need, therefore, for a reliable wireless location solution that does not require the assumption of either the distribution of the propagation delay estimate or any external source of positioning information, and that can provide a real-time robust detection technique, which can detect and reject the biased propagation delays regardless of either the distribution of the propagation delay estimates or the propagation environment.